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Abstract A051: Multi-omic explainable machine learning improves cancer treatment outcome prediction2025 Clinical Cancer Research conference-abstract Biochemistry, Genetics and Molecular Biology Breast Cancer Treatment Studies
Khoa Anh Tran, Venkateswar Addala, Lambros T. Koufariotis, Jia Zhang, Scott Wood, Conrad Leonard, +10 more
2citations -
MO386: Visualising and Differentiating Kidney Disorders by Urinary Peptidomics Using a Machine Learning Approach2022 Nephrology Dialysis Transplantation conference-abstract Medicine Chronic Kidney Disease and Diabetes
Justyna Siwy, Emmmanouil Mavrogeorgis, Tianlin He, Harald Mischak, Harald Rupprecht, Joachim Beige
1citations -
Abstract 4137423: Can Machine Learning Help Prioritise Who to Screen for Elevated Lipoprotein(a) (Lp[a]) in the General Population vs a Screen all Approach? An Analysis from UK Biobank
Christophe A. T. Stevens, Fotios Barkas, Julia Brandts, Sunganani Kwilasi, Alireza S. Mahani, Antonio J. Vallejo‐Vaz, +2 more
0citations -
OC19.04: A deep learning model for prenatal congenital heart disease screening generalises to a community setting and outperforms clinical detection2023 Ultrasound in Obstetrics and Gynecology conference-abstract Medicine Artificial Intelligence in Healthcare and Education Open access
Chinmayee Athalye, Amber E. L. van Nisselrooij, Syed Shamair Ali Rizvi, Monique C. Haak, Anita J. Moon‐Grady, Rima Arnaout
2citations -
Fully automatic deep learning pulmonary hypertension diagnosis using CT pulmonary angiography2022 13.01 - Pulmonary hypertension conference-abstract Medicine Pulmonary Hypertension Research and Treatments
Michael J. Sharkey, Kavita Karunasaagarar, C S Johns, Smitha Rajaram, K Dwivedi, P Garg, +9 more
1citations -
OC11.07: Automated grading of fetal cortical development using deep learning algorithms: a preliminary three‐dimensional ultrasound study in healthy fetuses2021 Ultrasound in Obstetrics and Gynecology conference-abstract Medicine Fetal and Pediatric Neurological Disorders
Madeleine K. Wyburd, Linde S. Hesse, Moska Aliasi, Felipe A. Moser, Monique C. Haak, Aris T. Papageorghiou, +1 more
0citations -
From Snapshots to Fluxes: Independent Wind Retrieval Algorithms for Next-Generation Multi-image Greenhouse Gas Satellites via Deep Learning2026 conference-abstract Environmental Science Atmospheric and Environmental Gas Dynamics Open access
Bastiaan van Diedenhoven, Piyushkumar N. Patel, Koen Reerink, Tobias Borsdorff, Jochen Landgraf
0citations -
Prediction of Poor Survival after Hematopoietic Cell Transplantation in Myelofibrosis Using Machine Learning Techniques2024 Blood conference-abstract Medicine Myeloproliferative Neoplasms: Diagnosis and Treatment Open access
Juan Carlos Hernández‐Boluda, Adrián Mosquera Orgueira, Luuk A. Gras, Linda Köster, Joe Tuffnell, Nicolaus Martin Kröger, +24 more
1citations -
Prediction of Severe Gastrointestinal Bleeding Events in Hemodialysis: Collaborative Development of Machine Learning Model Within INSPIRE2021 Journal of the American Society of Nephrology conference-abstract Medicine Dialysis and Renal Disease Management
Suman Kumar Lama, Sheetal Chaudhuri, Joanna L. Willetts, John W. Larkin, Anke C. Winter, Manuela Stauss‐Grabo, +6 more
0citations -
A Machine Learning Approach to Upscale Net Ecosystem Exchange to a Regional Scale: Integration of Eddy Covariance, Remote Sensing and Reanalysis Data2020 conference-abstract Environmental Science Plant Water Relations and Carbon Dynamics Open access
Oliver Reitz, Alexander Graf, Marius Schmidt, Gunnar Ketzler, Michael Leuchner
0citations